. Discuss four types of dependent measures and provide a concrete example of eac
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Question
. Discuss four types of dependent measures and provide a concrete example of each one. 5. Explain the difference between Type I and Type II Errors. Provide an example of each. 6. Why is random sampling used so infrequently in psychological research? What sampling method is more common? Does lack of random sampling pose problems for research? Why or why not? . What advantages do factorial designs have over single factor designs 8. How do between-subjects designs differ from within-subjects (or repeated measures) designs? Describe a hypothetical example of each type of design 9. Under what conditions should researchers consider using single participant experiments? 0.What is content validity? Provide an example and explain how it differs from criterion validity and concurrent validityExplanation / Answer
Answer for Question 4:
1. Nominal scale: Nominal scales are used for labeling variables, without any quantitative value. The values in these scales are mutually exclusive (no overlap) categories and do not have any numerical significance. For example, one’s hair colour is a nominal variable - it can be black, brown, blonde, red etc.
2. Ordinal scale: Ordinal scales are used for variables whose values allow it to be ranked, but the precise differences between is unknown. Ordinal scales are typically measures of non-numeric concepts that exist in varying degrees. For example, asking individuals how happy they are and ranking them based on three responses - very happy, slightly happy and OK.
3. Interval scales: Interval scales are used for numerical variables because in which the order of its variables are known along with the exact differences between the values. The classic example of an interval scale is Celsius temperature because the difference between each value is the same. However in interval scales, there is no absolute zero point. In case of the Celsius scale, 0 degrees doesn’t not indicate an absence of temperature.
4. Ratio scales: Ratio scales represent the highest level of measurement as they are used for variables that indicate the order, exact value between units, and also have an absolute zero–which allows for a wide range of both descriptive and inferential statistics to be applied. For example, height and weight is a variable that can be measured on the ratio scale.
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